CN115793091B - Weak interlayer identification method and device based on in-hole optical imaging and acoustic wave scanning - Google Patents
Weak interlayer identification method and device based on in-hole optical imaging and acoustic wave scanning Download PDFInfo
- Publication number
- CN115793091B CN115793091B CN202211419778.7A CN202211419778A CN115793091B CN 115793091 B CN115793091 B CN 115793091B CN 202211419778 A CN202211419778 A CN 202211419778A CN 115793091 B CN115793091 B CN 115793091B
- Authority
- CN
- China
- Prior art keywords
- hole wall
- image
- column
- acoustic wave
- response function
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000011229 interlayer Substances 0.000 title claims abstract description 76
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000012634 optical imaging Methods 0.000 title claims abstract description 28
- 238000005316 response function Methods 0.000 claims description 91
- 239000011159 matrix material Substances 0.000 claims description 62
- 239000011148 porous material Substances 0.000 claims description 43
- 238000001228 spectrum Methods 0.000 claims description 24
- 238000001514 detection method Methods 0.000 claims description 23
- 238000012545 processing Methods 0.000 claims description 20
- 238000012937 correction Methods 0.000 claims description 16
- 230000008569 process Effects 0.000 claims description 11
- 230000026683 transduction Effects 0.000 claims description 10
- 238000010361 transduction Methods 0.000 claims description 10
- 238000005286 illumination Methods 0.000 claims description 9
- 230000005540 biological transmission Effects 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000007781 pre-processing Methods 0.000 claims description 6
- 230000003595 spectral effect Effects 0.000 claims description 4
- 239000012774 insulation material Substances 0.000 claims description 3
- 238000005553 drilling Methods 0.000 abstract description 58
- 239000011435 rock Substances 0.000 description 28
- 230000003287 optical effect Effects 0.000 description 25
- 238000005516 engineering process Methods 0.000 description 16
- 238000005259 measurement Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 230000004044 response Effects 0.000 description 7
- 230000004927 fusion Effects 0.000 description 5
- 230000000007 visual effect Effects 0.000 description 5
- 238000003384 imaging method Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 239000012530 fluid Substances 0.000 description 3
- 229910000831 Steel Inorganic materials 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000003702 image correction Methods 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000035772 mutation Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000007639 printing Methods 0.000 description 2
- 230000006798 recombination Effects 0.000 description 2
- 238000005215 recombination Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000010959 steel Substances 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 239000004593 Epoxy Substances 0.000 description 1
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 description 1
- -1 acryl Chemical group 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
- 230000000712 assembly Effects 0.000 description 1
- 238000000429 assembly Methods 0.000 description 1
- 238000009412 basement excavation Methods 0.000 description 1
- 239000011324 bead Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 239000004568 cement Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013075 data extraction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 239000010410 layer Substances 0.000 description 1
- 229910052744 lithium Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000000877 morphologic effect Effects 0.000 description 1
- 239000004033 plastic Substances 0.000 description 1
- 229920003023 plastic Polymers 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000012113 quantitative test Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000000565 sealant Substances 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 239000002002 slurry Substances 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 229910001220 stainless steel Inorganic materials 0.000 description 1
- 239000010935 stainless steel Substances 0.000 description 1
- 238000000547 structure data Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 239000012780 transparent material Substances 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
- 230000003313 weakening effect Effects 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Abstract
The invention discloses a weak interlayer identification device based on in-hole optical imaging and acoustic wave scanning, which comprises an upper shell, wherein the top end of the upper shell is connected with a lifting cover, a power supply assembly, a collection assembly, a control assembly and an azimuth assembly are arranged in the upper shell, the bottom end of the upper shell is connected with the top end of a light source assembly, the bottom end of the light source assembly is connected with the top end of an acoustic wave assembly, the bottom end of the acoustic wave assembly is connected with the top end of a light-transmitting window, the bottom end of the light-transmitting window is connected with the top end of a camera shooting assembly, and the bottom end of the camera shooting assembly is connected with the top end of the lower shell. The invention also discloses a weak interlayer identification method based on the intra-hole optical imaging and the acoustic wave scanning, and the method fundamentally solves the technical problem of difficult weak interlayer identification in geological drilling.
Description
Technical Field
The invention relates to the field of geological structure survey, in particular to a weak interlayer identification device based on in-hole optical imaging and acoustic wave scanning, and further relates to a weak interlayer identification method based on in-hole optical imaging and acoustic wave scanning, which is suitable for observing, identifying and classifying rock mass structures in various geological fields, acquiring rock wall image information and acoustic response information of geological drilling holes, and can realize the identification of the weak interlayer in the geological drilling holes and facilitate the classification and evaluation of the rock mass structures.
Background
The weak structural surface in the rock mass has the characteristics of weak breaking, small thickness, easy disturbance, easy erosion and the like, and the strength and the rocks at two sides are obviously different, so that the spatial position and the shape of the weak structural surface are determined, and the difficulty of taking samples as engineering investigation is overcome. The conventional drilling method has low success rate of sampling the weak structural surface, and poor positioning and qualitative effects. The investigation method of large-caliber drilling or excavation of a exploratory hole and a vertical shaft is adopted, so that the construction period is long, the cost is high, and the safety is poor. In geological exploration, conventional drilling is a very mature exploration means, is simple, convenient and practical, but is an indirect means, and when complex geological conditions with low drilling coring rate are met, geological information of structural surfaces such as faults, weak surfaces, weak joints, weak bands and the like in the drilling are difficult to obtain, so that erroneous judgment on deep geological conditions is easy to cause. By using the drilling digital imaging technology, geological information in the drilling is more visual and clear. The digital imaging result can truly reflect the damage condition of the rock mass in the hole due to the influence of the structure, karst and sliding, and make up for the defect that the drilling means is not suitable for disclosing the condition of the sliding surface which has long occurrence and has very thin thickness of the sliding belt in the rock mass. Although the drilling digital imaging technology overcomes the defects of conventional geological drilling and provides more visual in-drilling geological information, as the drilling imaging technology only reflects the image characteristics of the surface of the rock wall of the drilling, the differential characteristics of the internal structure of the rock body of the drilling are not considered, the type of the structural surface is often difficult to identify, and more abundant data sources cannot be provided for the identification and analysis of the structural surface.
Therefore, in view of the technical problem that the type of the structural surface is judged in the aspect of image recognition in the current geological structure, the invention provides a weak interlayer recognition method and device based on in-hole optical imaging and acoustic scanning by means of the current mature high-tech means (optical imaging technology, acoustic scanning technology and the like), so that the measurement error caused by eccentricity in the detection process of the in-hole device is effectively weakened, the accuracy of the hole wall optical imaging and acoustic scanning test results is improved, more accurate data sources are provided for the weak interlayer recognition, the multi-element characteristic information of the hole wall is synchronously fused, and the technical problem of difficulty in recognizing the weak interlayer in geological drilling is fundamentally improved. The device combines an optical camera shooting technology, a sound wave dynamic scanning technology and a precise positioning technology, realizes the information organic pairing and fusion of hole wall images and rock wall reflection characteristics of geological drilling, realizes the complementation and mutual evidence of the respective advantages of multiple parameters by extracting multiple characteristic information parameters of a hole wall structure from the angles of optical images and sound wave scanning, simultaneously compensates the single data source problem of the traditional single parameter identification structure, combines the complementation characteristics of different data analysis methods, improves the accuracy and objectivity of the interpretation and interpretation of the structure data of the drilling rock mass, ensures the accuracy and reliability of weak interlayer identification, and provides scientific basis for the management of geological disasters.
The method and the device for recognizing the weak interlayer based on the intra-hole optical imaging and the acoustic wave scanning are provided, and based on the effective correction of data errors caused by detection eccentricity, the optical imaging technology, the acoustic wave measuring technology, the dynamic scanning technology and the accurate positioning technology are combined to realize the information organic pairing and fusion of the hole wall image of geological drilling and the rock wall reflection characteristic, the multi-element characteristic information parameters of the hole wall structure are extracted from the angle of the optical image and the acoustic wave scanning, the intra-hole weak interlayer recognition based on the multi-element data fusion is realized, and the recognition accuracy of the weak interlayer is greatly improved. The weak interlayer identification method and device based on the intra-hole optical imaging and the acoustic wave scanning have the advantages that: 1) The recognition accuracy is high. The accuracy of basic data is improved by effectively correcting error data caused by non-centering of the device in the actual detection process, and the common response characteristics of multiple parameters are synthesized from the characteristic parameters with different hole wall structures, so that the mutual supplement and mutual verification of the characteristic parameters of the weak interlayer are realized, and the instability of the traditional single identification method is improved; 2) And (5) data multiplexing. Through ingenious structural design and algorithm compensation, synchronous acquisition of visual image information and acoustic wave reflection information of a hole wall structure is realized, multiple characteristic parameters such as hole wall structure texture characteristics, hole wall structure integrity characteristics, echo signal time domain characteristics, echo signal frequency spectrum characteristics and the like are obtained, and the recognition process of a weak interlayer is ensured to have more diversified data parameters as recognition characteristics; 3) The data is more visual. By visualizing the optical image of the hole wall and the acoustic wave scanning data and combining a corresponding correction method, the morphological characteristics and acoustic response characteristics of the drilling surface can be more clearly presented, and simultaneously, the visualized presentation of the weak interlayer is realized by the multi-element data fusion of the weak interlayer,
Finally, the specific position and distribution characteristics of the weak interlayer can be intuitively presented; 4) The measurement mode is simple. The rapid acquisition of the optical images of the wall of the drill hole and the acoustic reflection characteristic data of the rock wall can be realized only by lowering the device to the region needing to be measured in the drill hole through the components such as the steel wire rope or the push rod, and the rapid identification of the weak interlayer can be realized by combining a subsequent data processing method; 5) The structure is small and exquisite, the overall arrangement is nimble, connects succinctly, easily implements.
Disclosure of Invention
The invention aims to solve the technical problem of difficult weak interlayer identification in geological drilling, provides a weak interlayer identification device based on in-hole optical imaging and acoustic wave scanning, and also provides a weak interlayer identification method based on in-hole optical imaging and acoustic wave scanning, which combines optical photographing, acoustic wave measurement, dynamic scanning and accurate positioning, thereby fundamentally solving the technical problem of difficult weak interlayer identification in geological drilling. The method and the device have novel conception and easy implementation, are a new method and a new generation device of geological drilling measurement technology, and have wide application prospect.
In order to achieve the above object, the present invention adopts the following technical measures:
the utility model provides a weak intermediate layer recognition device based on downthehole optical imaging and acoustic wave scanning, includes upper portion casing, upper portion casing top is connected with the promotion lid, is provided with power supply unit in the upper portion casing, gathers subassembly, control assembly and position subassembly, and the bottom and the light source subassembly top of upper portion casing are connected, and light source subassembly bottom and acoustic wave subassembly top, acoustic wave subassembly bottom and printing opacity window top are connected, and printing opacity window bottom and subassembly top of making a video recording are connected, and the bottom and the lower part casing top of making a video recording of subassembly are connected.
As described above, the upper shell is cylindrical, the light source component is annular, the sound wave component comprises a plurality of transduction transceivers, each transduction transceiver is annularly distributed, sound insulation materials are filled between adjacent transduction transceivers, the light transmission window is cylindrical, the upper part of the lower shell is cylindrical, and the lower part of the lower shell is cylindrical or hemispherical.
The sonic and camera assemblies have the same borehole wall monitoring ring as described above.
The weak interlayer identification method based on the intra-hole optical imaging and the acoustic wave scanning comprises the following steps:
step 1, acquiring an acoustic wave scanning matrix according to an acoustic wave assembly, and acquiring an expanded image of a hole wall according to a camera assembly;
step 2, determining a pore wall texture characteristic response function, a pore wall integrity characteristic response function, an echo signal time domain characteristic response function and an echo signal frequency spectrum characteristic response function according to the acoustic wave scanning matrix and the pore wall expansion image;
and step 3, carrying out weighted calculation on the hole wall texture characteristic response function value, the hole wall integrity characteristic response function value, the echo signal time domain characteristic response function value and the echo signal frequency spectrum characteristic response function value at the same depth to further obtain a borehole wall reconstruction image, and determining a weak interlayer region according to the borehole wall reconstruction image.
Step 1 as described above comprises the steps of:
step 1.1, processing a hole wall fisheye image obtained by a camera shooting assembly to obtain a hole wall unfolding image, which specifically comprises the following steps:
step 1.1.1, converting the hole wall fisheye image F acquired by the camera shooting assembly into a hole wall unfolding image F1, wherein the starting position of the hole wall unfolding image F1 corresponds to the hole wall image of the geographic north pole of the hole wall, the hole wall unfolding images F1 sequentially present hole wall images in different directions, the cut-off position of the hole wall unfolding image F1 corresponds to the hole wall image of the geographic north pole of the hole wall,
step 1.1.2, converting the hole wall expansion image F1 expressed by RGB into the hole wall expansion image expressed by HSV, obtaining a hole wall expansion image F2, extracting the arithmetic average value of brightness values of each column of pixel points of the hole wall expansion image F2, comparing the arithmetic average values of each column, determining the column number J corresponding to the maximum value in the arithmetic average value of each column,
step 1.1.3, preprocessing the hole wall expansion image F2 to form a hole wall expansion image F3, and recording the brightness value corresponding to each pixel point in the hole wall expansion image F2 before preprocessing as FV i,j The brightness value corresponding to each pixel point in the preprocessed hole wall expanded image F3 is FFV i,j
Wherein lambda is 1 For the illumination enhancement factor, i represents the row number, j represents the column number, N n Representing the total column number of the pixel point matrix of the hole wall expansion image F3;
the hole wall expansion image F3 expressed in HSV color space is converted into a hole wall expansion image F4 expressed in RGB color space.
Step 1 as described above further comprises the steps of:
step 1.2, processing ultrasonic scanning signals to obtain an acoustic scanning matrix, which specifically comprises the following steps:
step 1.2.1, rearranging M groups of ultrasonic scanning signals acquired at the same detection depth according to azimuth sequence to form an M+1 column of acoustic scanning matrix T, wherein the 1 st column of the acoustic scanning matrix T represents an acoustic scanning echo signal of the geographic north direction of the borehole wall, and the M+1 column of the acoustic scanning matrix T represents an acoustic scanning echo signal of the geographic north direction of the borehole wall;
step 1.2.2, forming an acoustic wave scanning matrix TT after correcting the acoustic wave scanning matrix T, and recording the amplitude value of each sound in the acoustic wave scanning matrix T before correcting to be V i,j Each sound amplitude value in the sound wave scanning matrix TT after correction processing is VV i,j ，
Wherein lambda is 2 For the sound amplitude enhancement coefficient, i represents a row number, j represents a column number, M+1 represents the total number of columns in the acoustic scan matrix T, INT () represents a rounding process, N n Representing the total column number of the pixel point matrix of the hole wall expansion image F3.
The pore wall texture feature response function in step 2 as described above is based on the following formula:
wherein: TF (j) represents a pore wall texture feature response function value corresponding to the j-th column of the pore wall expansion image F4, and the pore wall texture feature responseRepresenting the red image gradient corresponding to the j-th column of the hole wall expanded image F4; />Representing the green image gradient corresponding to the j-th column of the hole wall expanded image F4; />Representing the blue image gradient corresponding to the j-th column of the hole wall expanded image F4;
the pore wall integrity characteristic response function in the step 2 is based on the following formula:
wherein IF (j) represents a hole wall integrity feature response function value, max { S }, of a j-th column of the hole wall expansion image F4 r (j) The red gray maximum value corresponding to the RGB value of the j-th pixel point in the hole wall expanded image F4 is min { S }, and r (j) The red gray minimum value corresponding to the RGB value of the j-th pixel point in the hole wall expansion image F4 is } NN is the total line number of the pixel points in the hole wall expansion image F4, N n Representing the total number of columns of the matrix of pixel points of the hole wall expansion image F3,the average value S of blue gray scale corresponding to RGB value of j-th column pixel point in the hole wall unfolded image F4 b (m, n) is a blue gray value corresponding to the RGB value of the pixel point in the m-th row and n-th column in the hole wall expansion image F4;
The echo signal time domain characteristic response function in the step 2 is based on the following formula:
wherein CF (j) represents the time domain characteristic response function value of the echo signal corresponding to the j-th column echo signal in the acoustic wave scanning matrix TT, c is the sound velocity corresponding to the acoustic wave propagation medium in the borehole, D is the diameter of the upper shell, and D is the diameter of the geological borehole, t| j Representing the time corresponding to the first occurrence of echo of the jth column echo signal in the acoustic wave scanning matrix TT;
the echo signal spectrum characteristic response function in the step 2 is based on the following formula:
wherein AF (j) represents the spectral characteristic response function value of the echo signal corresponding to the j-th echo signal in the acoustic wave scanning matrix TT, fmax represents the maximum frequency corresponding to the bandwidth of the acoustic wave signal, fmin represents the minimum frequency corresponding to the bandwidth of the acoustic wave signal,E(f)| j and representing the acoustic characteristic function value corresponding to the j-th column echo signal in the acoustic wave scanning matrix TT.
Step 3 as described above comprises the steps of:
step 3.1, dividing the hole wall expansion image F4 into M+1 rows of equidistant hole wall sub-images to form normalized hole wall expansion images, wherein each row of hole wall sub-images comprises N n The pixel points of the column/M,
normalized hole wall expanded image each row of hole wall texture feature response function value takes N corresponding to hole wall expanded image F4 n An average value of pore wall texture characteristic response function values of M columns of pixel points,
the pore wall integrity characteristic response function value of each row of normalized pore wall expansion image is obtained as the average value of the pore wall integrity characteristic response function values of N/M rows of pixel points corresponding to the pore wall expansion image F4, the pore wall azimuth angle represented by each row of image is 2 pi/M,
step 3.2, obtaining a borehole wall reconstruction image F5 based on the following formula:
F5(p,q)＝δ 1 ·TF(p,q)+δ 2 ·IF(p,q)+δ 3 ·AF(p,q)+δ 4 ·CF(p,q)
wherein delta 1 、δ 2 、δ 3 、δ 4 Weighting values, delta, respectively, of different response functions 1 +δ 2 +δ 3 +δ 4 =1, F5 (p, q) is the pixel value of the depth p column number q of the borehole wall reconstruction image, TF (p, q) is the hole wall texture feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, IF (p, q) is the hole wall integrity feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, AF (p, q) is the echo signal spectral feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, CF (p, q) is the echo signal time domain feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q,
step 3.3, if the average value of pixels of a certain depth of the borehole wall reconstruction image F5 is smaller than a set threshold value, the depth is considered to be a weak interlayer region; if the average value of the pixels of a depth of the borehole wall reconstruction image F5 is greater than or equal to a set threshold, the depth is considered to be a non-weak region.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, visual detection and acoustic wave detection are combined, so that the visualization of the hole wall morphology of the inner wall of the geological borehole is realized, the quantitative test of the acoustic reflection characteristic of the rock wall is realized, the multi-element information such as the hole wall structure texture characteristic, the hole wall structure integrity characteristic, the echo signal time domain characteristic, the echo signal frequency spectrum characteristic and the like of the geological borehole can be rapidly captured, the presentation characteristic of the rock mass structure can be mastered from different angles, the multi-element characteristic parameters are provided for the identification of the weak interlayer, and the problem of accurate identification of the weak interlayer can be effectively solved;
2. the sensor based on the technical principle and the device is simple, the cost of the sensor corresponding to optical photographing, acoustic dynamic scanning and accurate positioning is low, the universality is high, and the device is easy to replace after being partially damaged;
3. the method has higher efficiency in data processing, can rapidly realize multi-element data extraction of the geological drilling through a small amount of data processing, synchronously presents optical image information and acoustic wave scanning information of the geological drilling, and finally can intuitively present specific positions and distribution characteristics of the weak interlayers;
4. The device is convenient to operate and easy to realize, the obtained data is more abundant, the obtained result is more reliable, and the measurement efficiency is greatly improved;
the invention has simple structure system and overall layout and is easy to implement.
In a word, the invention provides a weak interlayer identification method and device based on hole optical imaging and acoustic scanning by utilizing optical photographing, acoustic measurement, dynamic scanning and accurate positioning, which fundamentally solve the technical problem of difficult weak interlayer identification in geological drilling, improve the accuracy of hole wall optical imaging and acoustic scanning test results by effectively weakening measurement errors caused by eccentricity in the detection process of devices in the drilling, provide more accurate data sources for weak interlayer identification, synchronously realize the organic pairing and fusion of hole wall images and rock wall reflection characteristics of the geological drilling, and realize mutual complementation and mutual verification of the advantages of multiple parameters by extracting multi-element characteristic information parameters of a hole wall structure from the angles of optical images and acoustic scanning, and simultaneously make up the problem of single data sources of the traditional single-parameter identification structure, combine the complementary characteristics of different data analysis methods, improve the measurement failure condition caused by the fact that a detection device is not centered, and greatly improve the adaptability of the whole device. The method and the device have ingenious design, strict conception, simple structure system and easy implementation.
Drawings
FIG. 1 is a block diagram of the apparatus of the present invention;
FIG. 2 is a schematic diagram of an acoustic wave assembly;
FIG. 3 is a schematic diagram of a detection zone;
FIG. 4 is a schematic diagram of a probing process;
FIG. 5 is an example diagram of an expanded image of a hole wall;
FIG. 6 is a schematic view of illumination of a hole wall;
FIG. 7 is a diagram showing an example of the hole wall expansion image F1 to the hole wall expansion image F4;
FIG. 8 is a diagram illustrating the recombination of scan signals;
FIG. 9 is a schematic diagram of matrix normalization;
FIG. 10 is a schematic view of a feature image reconstruction;
in the figure: 1-lifting a cover; 2-an upper housing; 3-a power supply assembly; 4-an acquisition assembly; 5-a control assembly; a 6-azimuth assembly; 7-a light source assembly; an 8-sonic assembly; 9-a light-transmitting window; 10-a camera assembly; 11-lower housing.
Detailed Description
The present invention will be further described in detail below in conjunction with the following examples, for the purpose of facilitating understanding and practicing the present invention by those of ordinary skill in the art, it being understood that the examples described herein are for the purpose of illustration and explanation only and are not intended to limit the invention.
Example 1:
as shown in figures 1-3, the weak interlayer recognition device based on in-hole optical imaging and acoustic wave scanning comprises a lifting cover 1, an upper shell 2, a power supply assembly 3, an acquisition assembly 4, a control assembly 5, an azimuth assembly 6, a light source assembly 7, an acoustic wave assembly 8, a light transmission window 9, a camera shooting assembly 10 and a lower shell 11, wherein the lifting cover 1 is conical and is positioned at the top of the device and is mainly used for fixing a steel wire rope or a push rod and the like to realize the lowering and lifting actions of the whole device, the top end of the upper shell 2 is connected with the lifting cover 1, the upper shell 2 is cylindrical and is mainly used for protecting the internal power supply assembly 3, the acquisition assembly 4, the control assembly 5 and the azimuth assembly 6, the upper shell 2 can prevent external fluid from entering the cylinder and play a role of protecting internal circuits, the power supply assembly 3 is mainly used for protecting a lithium battery and a power supply control circuit and providing a stable power supply for the whole device, the collecting component 4 mainly realizes the management and storage of the collecting signals of the device, the control component 5 is respectively connected with the collecting component 4, the azimuth component 6, the light source component 7, the sound wave component 8 and the camera shooting component 10, the control component 5 mainly realizes the cooperative control among a plurality of components of the whole device, the azimuth component 6 mainly realizes the azimuth signal collection of the device, effectively grasps the geographic azimuth of the fixed position of the device, the bottom end of the upper shell 2 is connected with the top end of the light source component 7, the light source component 7 is in a circular ring shape and mainly consists of a plurality of LED lamp beads and circuits, and can be soaked in water for normal work through the treatment of a waterproof technology, the bottom end of the light source component 7 is connected with the top end of the sound wave component 8, the sound wave component 8 comprises a plurality of transduction transceivers, each transduction transceiver is in annular distribution, sound insulation materials are filled between the adjacent transduction transceivers, if soft plastics or epoxy etc. absorb stronger material of sound wave, prevent signal interference between the adjacent transduction transceiver, sound wave subassembly 8 bottom is connected with light-transmitting window 9 top, and light-transmitting window 9 is cylindricly, and light-transmitting window 9 bottom is connected with the subassembly 10 top of making a video recording, and subassembly 10 is made up mainly of fisheye camera and circuit, and the bottom of subassembly 10 of making a video recording is connected with lower part casing 11 top, and lower part casing 11 upper portion is cylindric, and lower part casing 11 lower part is cylinder platform or hemispherical.
The lifting cover 1, the upper shell 2, the light source assembly 7, the sound wave assembly 8, the light transmission window 9, the camera shooting assembly 10 and the lower shell 11 can form a closed cylinder, so that the whole device can bear the fluid pressure in an external test environment, and the fluid cannot enter the device. Sealing ring components are arranged among the components, such as: o-rings or sealants, etc.
The lift cap 1 and the upper housing 2 are usually formed by processing a nonmagnetic material such as stainless steel.
The number of the acoustic wave components 8 is mainly determined according to the acoustic wave characteristic parameters and the cost, the higher the frequency of the acoustic wave transducer is, the smaller the size of the array elements is, the larger the number of the array elements which can be laid is, the lower the frequency of the acoustic wave transducer is, the larger the size of the array elements is, and the smaller the number of the array elements which can be laid is.
The light-transmitting window 9 is usually made of transparent material such as glass or acryl.
The light source assembly 7, the sound wave assembly 8, the light transmission window 9, the subassembly 10 makes a video recording, through mechanical size adjustment, ensure when the device is located drilling central point put, namely the central axis of device and the central axis coincidence of drilling, the drilling pore wall region that the light source assembly 7 can illuminate is regional A, regional A that covers is the ring banding, the drilling pore wall region that the sound wave assembly 8 can gather is regional B's sound wave signal, regional B that covers is the ring banding, the drilling pore wall region that the subassembly 10 can gather is regional C's optical image, regional C that covers is the ring banding, regional A overlaps with regional C's region is regional B, thereby guarantee that the device has uniformity through the regional correspondence that sound wave signal and image information that the sound wave assembly 8 and the subassembly 10 gathered were made a video recording correspond.
As shown in fig. 4, if the drilling area to be detected is a rock mass structure between the drilling depth Z1 and the drilling depth Z2, the detection can be performed by the descending device, which is the sequential detection from the drilling depth Z1 to the drilling depth Z2, or the detection can be performed by the ascending device, which is the sequential detection from the drilling depth Z2 to the drilling depth Z1, if the detection is performed by the descending device, a main workflow of the weak interlayer recognition device based on the in-hole optical imaging and the acoustic wave scanning is as follows:
(1) The assembled device is quickly lowered to the position with the depth Z1 of the drilling hole to be detected by external tools such as a cable or a push rod, and after the acoustic wave component 8 of the device is lowered to the position with the depth Z1 of the drilling hole, the device is suspended for a certain time,
(2) The sound wave component 8 controls M annular transducers to point to corresponding vertical rock walls to emit sound wave signals, the M annular transducers synchronously receive the sound wave signals reflected by the rock walls, the camera component 10 collects hole wall optical images, the azimuth component 6 collects geographic azimuth signals corresponding to the fixed positions of the device, the collecting component 4 completes synchronous collection of M groups of sound wave signals, optical images and geographic azimuth signals at the drilling depth Z1,
(3) After the signal acquisition at the drilling depth Z1 is completed, slowly lowering the device, repeating the step (2) and the step (3) after the acoustic wave assembly 8 is lowered to the position with the drilling depth of Z1+Deltah, and sequentially completing the acoustic scanning and the optical image hole wall information detection of a plurality of horizontal sections from the drilling depth Z1 to the drilling depth Z2
(4) After the detection is completed, the device is quickly lifted, the recovery of the device is realized, the data stored by the acquisition component 4 is subjected to subsequent processing,
in the above test process, the lowering positions of the components of the device can be calculated by the lowering depths of the cable and the push rod, in the whole detection process, an additional device is needed to record the initial working depth of the device, the initial position of the device is judged by the video collected by the camera assembly 10, thereby realizing the depth correction between the collected data and the real data, realizing the correspondence between the detection information and the real depth information,
example 2:
the weak interlayer identification method based on the in-hole optical imaging and the acoustic wave scanning, which uses the data acquired by the weak interlayer identification device based on the in-hole optical imaging and the acoustic wave scanning described in the embodiment 1, mainly comprises the following steps: m sets of acoustic signals S, optical images F and geographic orientation signals a,
The weak interlayer identification method based on the intra-hole optical imaging and the acoustic wave scanning mainly comprises the following steps:
step 1, correcting drilling data, mainly avoiding data errors caused by eccentricity in the detection process of the device, and improving the quality of hole wall optical images and acoustic wave scanning data. Mainly comprises the following steps:
step 1.1, processing the hole wall fisheye image obtained by the camera component 10 to obtain a hole wall unfolding image, mainly comprising the following steps:
step 1.1.1, hole wall image expansion, mainly comprising the following steps:
as shown in fig. 5, the acquired hole wall fisheye image F is converted into a hole wall unfolding image F1 by combining digital image processing technology, interpolation technology and the like with geographic azimuth a, wherein the starting position of the hole wall unfolding image F1 corresponds to the hole wall image of the geographic north pole of the hole wall, the hole wall unfolding images F1 sequentially present hole wall images in different azimuth, the cut-off position of the hole wall unfolding image F1 corresponds to the hole wall image of the geographic north pole of the hole wall,
as shown in FIG. 6, the more the device is deviated to the wall of a borehole, the stronger the illumination received by the wall part of the borehole is, and the clearer the corresponding optical image of the wall of the borehole is; the farther the device is away from the wall of the borehole, the weaker the illumination received by the wall part of the borehole is, the more the corresponding wall optical image is blurred, the wall optical expanded image is brighter, the stronger the illumination intensity is represented, the darker the color is represented, the weaker the illumination intensity is represented, by establishing an illumination geometric model, the relationship that the vertical distance between the device and the wall is changed along the circumferential direction is shown by a trigonometric function can be seen, the position of the device closest to the wall has the highest brightness of the corresponding wall optical image, the position of the device farthest from the wall has the lowest brightness of the corresponding wall optical image,
Step 1.1.2, image brightness positioning, mainly comprising the following steps:
as shown in fig. 7, the hole wall expansion image F1 expressed by RGB is converted into the hole wall expansion image expressed by HSV, the hole wall expansion image expressed by brightness value is recorded as a hole wall expansion image F2, the arithmetic average value of brightness values of each column of pixel points of the hole wall expansion image F2 is extracted, the arithmetic average value of each column is subjected to size comparison, the column number J corresponding to the maximum value in each column of the arithmetic average value is determined, the column number J represents the column number of the image pixel points corresponding to the position of the nearest hole wall of the device, the image brightness positioning of the device in the eccentric state is realized by determining the column number J, the correction reference parameter is provided for the hole wall image correction in the step 1.1.3,
step 1.1.3, hole wall image correction, mainly comprising the following steps:
preprocessing the hole wall expansion image F2 to form a hole wall expansion image F3, and if brightness values corresponding to all pixel points in the hole wall expansion image F2 before preprocessing are FV i,j The brightness value corresponding to each pixel point in the preprocessed hole wall expanded image F3 is FFV i,j The corresponding relation between the brightness value pretreatment before and after the pretreatment is as follows:
wherein lambda is 1 The illumination enhancement coefficient can be adjusted according to actual conditions, and is usually 0.5; i represents a row number, j represents a column number, N n The total column number of the pixel point matrix of the hole wall expansion image F3 is represented, the column number J represents the column number of the image pixel point corresponding to the position of the device closest to the hole wall, the column number is determined by the step 1.1.2, after the pretreatment from the hole wall expansion image F2 to the hole wall expansion image F3 is completed, the hole wall expansion image F3 represented by HSV color space is converted into the hole wall expansion image F4 represented by RGB color space, namely the correction processing of the hole wall image is completed, the bright and dark stripe phenomenon on the hole wall optical image disappears through the correction processing of the image, the pore structure on the image is clearer, clear digital image information can be provided for the identification of the weak interlayer in the hole wall image, the optical image deviation caused by the eccentricity of the device is effectively reduced,
step 1.2, processing ultrasonic scanning signals to obtain an acoustic scanning matrix, mainly comprising the following steps:
step 1.2.1, scanning signal recombination, mainly comprising the following steps of;
as shown in fig. 8, in combination with azimuth data of geographic azimuth a, by performing azimuth conversion on array element distribution, rearranging M groups of ultrasonic scanning signals acquired at the same detection depth according to azimuth sequence to form an m+1 column of acoustic scanning matrix T, where the azimuth corresponding to the acoustic scanning matrix T is in turn N (north), E (east), S (south), W (west) and N (north), the acoustic scanning matrix T comprises acoustic scanning echo signals of all-directional hole walls, a geographic azimuth included angle represented between two adjacent columns of acoustic scanning echo signals of the acoustic scanning matrix T is 2 pi/M, a first column of the acoustic scanning matrix T represents acoustic scanning echo signals of the geographic north azimuth of the hole wall of the hole, a (m+1) column of the acoustic scanning matrix T represents acoustic scanning echo signals of the geographic north azimuth of the hole wall of the hole, the first column of the acoustic scanning matrix T is identical to the m+1 column of acoustic scanning echo signals of the acoustic scanning matrix T, each column of the acoustic scanning matrix T represents a group of acoustic echo signals, a transverse zero point of the echo signals represents an acoustic amplitude, a transverse zero point represents a longitudinal amplitude, a transverse zero point represents a horizontal zero point represents a vertical amplitude, a negative zero point represents a vertical amplitude, a vertical zero point represents a vertical amplitude and a vertical time represents a vertical time-increasing time,
Step 1.2.2, scanning signal correction, specifically comprising the following steps:
since the positions of the acoustic wave assembly 8 and the image pickup assembly 10 are relatively fixed, the acoustic wave assembly 8 and the detection area of the image pickup assembly 10 are basically consistent, in the correction of the scanning signal, the correction parameter J in the image brightness positioning is used as the characteristic parameter of the correction of the scanning signal,
the acoustic wave scanning matrix T is corrected to form an acoustic wave scanning matrix TT, and if the amplitude value of each sound in the acoustic wave scanning matrix T before correction is V i,j Each sound amplitude value in the sound wave scanning matrix TT after correction processing is VV i,j The correspondence between before and after the correction processing is:
wherein lambda is 2 The sound amplitude enhancement coefficient can be adjusted according to actual conditions, and is usually 0.5; i denotes a row number, j denotes a column number, m+1 denotes the total number of columns in the acoustic scan matrix T, INT () denotes a rounding process, N n Representing the moment of F3 pixel point of the hole wall expansion imageThe total column number of the array, the column number J represents the column number of image pixel points corresponding to the position of the device closest to the hole wall, is determined by the step 1.1.2, and after the correction processing of scanning signals corresponding to the hole walls in different positions is completed, the acoustic amplitude values can be corrected to different degrees according to the actual geometric relationship, so that the acoustic amplitude error of echo signals caused by eccentricity of the device is weakened, more accurate acoustic echo information is provided for identifying weak interlayers by using the hole wall acoustic signals,
Step 2, extracting characteristic parameters, which mainly comprises the following steps:
the feature parameter extraction is mainly based on the expanded image F4 and the acoustic wave scanning matrix TT of the hole wall, and the texture feature, the integrity feature, the echo signal time domain feature and the echo signal frequency spectrum feature information of the hole wall structure are extracted from the angle of optical image and acoustic wave scanning, so the feature parameter extraction mainly comprises: step 2.1, extracting a pore wall texture characteristic response function value; step 2.2, extracting a hole wall integrity characteristic response function value; step 2.3, extracting the time domain characteristic response function value of the echo signal; step 2.4, extracting four steps of echo signal frequency spectrum characteristic response function values,
step 2.1, determining a pore wall texture characteristic response function TF, which mainly comprises the following steps of;
the difference between the filling composition of the weak interlayer and the non-weak interlayer is that the difference exists between the texture characteristics of the hole wall, therefore, the difference between the composition of rock mass and the degree of filling cement is described by constructing a texture characteristic response function TF of the hole wall, and the calculation expression of the texture characteristic response function TF of the hole wall is as follows:
wherein: TF (j) represents a pore wall texture feature response function value corresponding to the j-th column of the pore wall expansion image F4, and the pore wall texture feature response Representing the red image gradient corresponding to the j-th column of the hole wall expanded image F4;/>representing the green image gradient corresponding to the j-th column of the hole wall expanded image F4; />Representing the corresponding blue image gradient of the j-th column of the hole wall expansion image F4, the smaller the value of the hole wall texture characteristic response function TF is, the more obvious the corresponding texture mutation is, the larger the value of the hole wall texture characteristic response function TF is, the less obvious the corresponding texture mutation is,
step 2.2, determining a hole wall integrity characteristic response function, which mainly comprises the following steps:
the complete rock mass structure has a certain thickness and is represented as a continuity of gray values on the image, and the weak interlayer has a certain discontinuity. For this purpose, the difference of the gray value continuity of the rock mass image is described by constructing a hole wall integrity feature response function IF, and the calculation expression of the hole wall integrity feature response function IF is as follows:
wherein IF (j) represents a hole wall integrity feature response function value, max { S }, of a j-th column of the hole wall expansion image F4 r (j) The red gray maximum value corresponding to the RGB value of the j-th pixel point in the hole wall expanded image F4 is min { S }, and r (j) The red gray minimum value corresponding to the RGB value of the j-th pixel point in the hole wall expansion image F4 is } NN is the total line number of the pixel points in the hole wall expansion image F4, N n Representing the total number of columns of the matrix of pixel points of the hole wall expansion image F3,the average value S of blue gray scale corresponding to RGB value of j-th column pixel point in the hole wall unfolded image F4 b (m, n) is blue gray value corresponding to RGB value of mth row and nth column pixel points in the hole wall expansion image F4, and the smaller the value of the hole wall integrity characteristic response function IF is, the more accurate the position of the hole wall isThe worse the corresponding wall integrity, the greater the value of the pore wall integrity characteristic response function IF, the better the corresponding wall integrity,
step 2.3, determining the echo signal time domain characteristic response function, mainly comprising the following steps:
under the condition that the drilling outline is in a representation circle, the sound wave energy attenuation of sound waves in different directions is more consistent, and the weak interlayer and the non-weak interlayer can be effectively distinguished according to the difference characteristics of energy, however, when the drilling outline is in a non-standard circle, such as a blocking phenomenon, under the condition that the sound wave propagation distance is farther or closer, the energy change of the sound waves is different from the energy change of the normal position, so that the effective identification of the weak interlayer is easily affected, and therefore, the drilling outline characteristics of a measurement area are reflected by establishing an echo signal time domain characteristic response function CF, and the calculation expression of the echo signal time domain characteristic response function CF is as follows:
Wherein CF (j) represents the time domain characteristic response function value of the echo signal corresponding to the j-th column echo signal in the acoustic wave scanning matrix TT, c is the sound velocity corresponding to the acoustic wave propagation medium in the borehole, if the acoustic wave medium in the borehole is in a non-slurry environment, generally 1480m/s is taken, D is the diameter of the upper shell, D is the diameter of the geological borehole, t| j The time corresponding to the first occurrence of echo of the j-th echo signal in the acoustic wave scanning matrix TT is represented by the time used for the round trip of the acoustic wave signal, t| j The first echo may be determined by thresholding and energy methods, i.e. by the maximum peak value or energy maximum value of the first echo signal,
step 2.4, determining an echo signal spectrum characteristic response function;
in the aspect of acoustic characteristics of the rock wall, a certain difference characteristic exists between the soft interlayer and the non-soft interlayer in the aspect of acoustic response characteristics, the key of distinguishing the soft interlayer and the non-soft interlayer is to search an acoustic characteristic function of the rock, the power spectrum of ultrasonic waves has the characteristics of highlighting the main frequency and reflecting the energy power distribution of signals, and the acoustic response characteristic of the hole wall is reflected by establishing an echo signal spectrum characteristic response function AF. If the time domain signal of the collected echo signal is F (t), t is a time variable, FFT is adopted for analysis, and the expression of the power spectrum function G (F) is as follows:
Wherein T is the sample length in FFT transformation, F (F) is the waveform function of the echo signal F (T) in the acoustic wave scanning matrix TT after Fourier transformation, F is the frequency variable, and the power spectrum reflects the energy distribution in the frequency domain according to the physical meaning of spectrum analysis. The frequency spectrum is high, the sound attenuation of the rock on the surface section to the frequency is small, the received signal is strong, and conversely, the frequency spectrum is low, the attenuation is large, and the received signal is weak. In order to extract the characteristic information of the received echo signal more accurately, an acoustic characteristic function E (f) is constructed, and the acoustic characteristic function is defined as:
wherein f 1 For the minimum frequency value of the normal operating bandwidth of the transducer in the acoustic assembly 8, f 2 G (f) is the power spectrum function, which is the maximum frequency value of the normal operating bandwidth of the transducer in the acoustic assembly 8. In order to make the acoustic feature function independent of the absolute amplitude of the ultrasonic echo signal, only the relative variation of the echo signal frequency is extracted, and the analyzed echo signal needs to be normalized. The acoustic response characteristics corresponding to different rocks are different, the echo signal spectrum characteristic response function AF is reflected through an area enclosed between the acoustic characteristic function E (f) and a frequency axis, and the calculation expression of the echo signal spectrum characteristic response function AF is as follows:
Wherein AF (j) represents the acoustic wave scan matrix TTThe frequency spectrum characteristic response function value of the echo signal corresponding to the j-th column echo signal, fmax represents the maximum frequency corresponding to the bandwidth of the sound wave signal, fmin represents the minimum frequency corresponding to the bandwidth of the sound wave signal, and E (f) | j The acoustic feature function value corresponding to the j-th column echo signal in the acoustic wave scanning matrix TT is represented,
and 3, judging the weak area.
The position information of the weak interlayer in the rock mass structure of the drilling hole is highlighted through the texture characteristic response function TF, the hole wall integrity characteristic response function IF, the echo signal time domain characteristic response function CF and the echo signal frequency spectrum characteristic response function AF of the hole wall, so that the effective identification of the weak interlayer is realized, and the weak area judgment mainly comprises the following steps: step 3.1, normalizing the matrix; step 3.2, reconstructing a characteristic image; step 3.3, judging the weak area,
step 3.1, matrix normalization, mainly comprising the following steps:
as shown in FIG. 9, in order to ensure the consistency of array information between the optical image information and the acoustic wave scanning information, the hole wall expansion image F4 is divided into M+1 rows of equidistant hole wall sub-images to form normalized hole wall expansion images, wherein each row of hole wall sub-images comprises N n The response function TF of the texture characteristics of the pore wall corresponding to the normalized pore wall expanded image is also changed from the original N n The columns are converted into M+1 columns, and N corresponding to the pore wall expansion image F4 is obtained according to the pore wall texture characteristic response function value of each column of the normalized pore wall expansion image n The average value of the pore wall texture characteristic response function values of the pixel points in the column/M is the same as that in the column 1 and the column M+1.
Step 3.2, reconstructing a characteristic image, which mainly comprises the following steps:
as shown in fig. 10, on the basis of a hole wall expansion image F4, a hole wall texture feature response function TF, a hole wall integrity feature response function IF, an echo signal time domain feature response function CF, and an echo signal frequency spectrum feature response function AF of the normalized hole wall expansion image are fused, a corresponding hole wall feature image is reconstructed, a hole wall reconstruction image F5 considering various hole wall features is constructed, and the calculation expression is as follows:
F5(p,q)＝δ 1 ·TF(p,q)+δ 2 ·IF(p,q)+δ 3 ·AF(p,q)+δ 4 ·CF(p,q)
wherein delta 1 、δ 2 、δ 3 、δ 4 The weighting values of different response functions are respectively obtained, the average value is usually obtained, the weighting values can be properly adjusted according to the actual situation, and meanwhile, the four parameters also need to meet delta 1 +δ 2 +δ 3 +δ 4 The basic requirement of=1, F5 (p, q) is the pixel value of the depth p column number q of the borehole wall reconstruction image, TF (p, q) is the hole wall texture feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, IF (p, q) is the hole wall integrity feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, AF (p, q) is the echo signal spectrum feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, CF (p, q) is the echo signal time domain feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, p represents different depths, and q represents different columns.
Step 3.3, judging a weak area, which mainly comprises the following steps:
the gray scale treatment of 256 values is carried out on the reconstructed image F5 of the borehole wall, the smaller the pixel average value of the reconstructed image F5 of the borehole wall corresponding to a certain depth is, the greater the possibility that the depth corresponds to a weak interlayer is, namely, the darker the reconstructed image F5 of the borehole wall is, the higher the probability that the corresponding weak interlayer is, the larger the pixel average value of the reconstructed image F5 of the borehole wall corresponding to a certain depth is, the smaller the possibility that the depth corresponds to a weak interlayer is, namely, the brighter the reconstructed image F5 of the borehole wall is, the lower the probability that the corresponding weak interlayer is, namely, the judgment of the weak interlayer can be realized by comparing the average values of different depths with a set threshold, if the pixel average value of the reconstructed image F5 of the borehole wall is smaller than the set threshold, the depth is considered as a weak interlayer region, and if the pixel average value of the reconstructed image F5 of the depth of the borehole wall is larger than or equal to the set threshold, the depth is considered as a non-weak region, wherein the set threshold is the size lambda a *256，λ a Is a range of values of (a)Between 0 and 1 lambda a Typically 0.8, lambda a Can be properly adjusted according to specific conditions, and if the weak interlayer has great influence on the research of the whole geologic body, the weak interlayer has higher recognition requirement and lambda a The value of (2) can be set smaller, if the research influence of the weak interlayer on the whole geologic body is not obvious, only the main and obvious weak interlayer, lambda, needs to be identified a In addition, the identification of the weak interlayer can be realized by combining the subsequent image processing, the distinction between the weak interlayer and the non-weak interlayer in the geological drilling hole can be realized by carrying out binarization processing on the reconstructed image F5 of the wall of the drilling hole, the weak interlayer in the geological drilling hole is represented by a black area, and the non-weak interlayer area in the geological drilling hole is represented by a white area, so that a reference basis is provided for judging the structural surface of the rock mass.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Claims (4)
1. The weak interlayer identification method based on the in-hole optical imaging and the acoustic wave scanning utilizes a weak interlayer identification device based on the in-hole optical imaging and the acoustic wave scanning, the device comprises an upper shell (2), the top end of the upper shell (2) is connected with a lifting cover (1), a power supply component (3), a collecting component (4), a control component (5) and an azimuth component (6) are arranged in the upper shell (2), the bottom end of the upper shell (2) is connected with the top end of a light source component (7), the bottom end of the light source component (7) is connected with the top end of an acoustic wave component (8), the bottom end of the acoustic wave component (8) is connected with the top end of a light transmission window (9), the bottom end of the light transmission window (9) is connected with the top end of a camera shooting component (10), the bottom end of the camera shooting component (10) is connected with the top end of a lower shell (11),
the upper shell (2) is cylindrical, the light source component (7) is annular, the sound wave component (8) comprises a plurality of transduction transceivers, each transduction transceiver is annularly distributed, sound insulation materials are filled between adjacent transduction transceivers, the light transmission window (9) is cylindrical, the upper part of the lower shell (11) is cylindrical, the lower part of the lower shell (11) is cylindrical or hemispherical,
the method is characterized by comprising the following steps:
step 1, acquiring an acoustic wave scanning matrix according to an acoustic wave assembly (8), and acquiring an expanded hole wall image according to a camera assembly (10);
Step 2, determining a pore wall texture characteristic response function, a pore wall integrity characteristic response function, an echo signal time domain characteristic response function and an echo signal frequency spectrum characteristic response function according to the acoustic wave scanning matrix and the pore wall expansion image;
step 3, weighting calculation is carried out on the hole wall texture characteristic response function value, the hole wall integrity characteristic response function value, the echo signal time domain characteristic response function value and the echo signal frequency spectrum characteristic response function value of the same depth, a borehole wall reconstruction image is further obtained, a weak interlayer region is determined according to the borehole wall reconstruction image,
the step 1 comprises the following steps:
step 1.1, processing the hole wall fisheye image obtained by the camera shooting assembly (10) to obtain a hole wall unfolding image, which specifically comprises the following steps:
step 1.1.1, converting the hole wall fisheye image F acquired by the camera shooting assembly (10) into a hole wall unfolding image F1, wherein the starting position of the hole wall unfolding image F1 corresponds to the hole wall image of the geographic north pole of the hole wall, the hole wall unfolding images F1 sequentially present hole wall images in different directions, the cut-off position of the hole wall unfolding image F1 corresponds to the hole wall image of the geographic north pole of the hole wall,
step 1.1.2, converting the hole wall expansion image F1 expressed by RGB into the hole wall expansion image expressed by HSV, obtaining a hole wall expansion image F2, extracting the arithmetic average value of brightness values of each column of pixel points of the hole wall expansion image F2, comparing the arithmetic average values of each column, determining the column number J corresponding to the maximum value in the arithmetic average value of each column,
Step 1.1.3, preprocessing the hole wall expansion image F2 to form a hole wall expansion image F3, and recording the brightness value corresponding to each pixel point in the hole wall expansion image F2 before preprocessing as FV i,j The brightness value corresponding to each pixel point in the preprocessed hole wall expanded image F3 is FFV i,j
Wherein lambda is 1 For the illumination enhancement factor, i represents the row number, j represents the column number, N n Representing the total column number of the pixel point matrix of the hole wall expansion image F3;
the hole wall expansion image F3 expressed in HSV color space is converted into a hole wall expansion image F4 expressed in RGB color space.
2. The method for identifying a weak interlayer based on intra-hole optical imaging and acoustic wave scanning according to claim 1, wherein the step 1 further comprises the steps of:
step 1.2, processing M groups of ultrasonic scanning signals acquired at the same detection depth to obtain an acoustic scanning matrix, and specifically comprising the following steps:
step 1.2.1, rearranging M groups of ultrasonic scanning signals acquired at the same detection depth according to azimuth sequence to form an M+1 column of acoustic scanning matrix T, wherein the 1 st column of the acoustic scanning matrix T represents an acoustic scanning echo signal of the geographic north direction of the borehole wall, and the M+1 column of the acoustic scanning matrix T represents an acoustic scanning echo signal of the geographic north direction of the borehole wall;
Step 1.2.2, forming an acoustic wave scanning matrix TT after correcting the acoustic wave scanning matrix T, and recording the amplitude value of each sound in the acoustic wave scanning matrix T before correcting to be V i,j Each sound amplitude value in the sound wave scanning matrix TT after correction processing is VV i,j ，
Wherein lambda is 2 For the sound amplitude enhancement coefficient, i represents a row number, j represents a column number, M+1 represents the total number of columns in the acoustic scan matrix T, INT () represents a rounding process, N n Representing the total column number of the pixel point matrix of the hole wall expansion image F3.
3. The method for identifying weak interlayers based on intra-hole optical imaging and acoustic wave scanning according to claim 2, wherein the hole wall texture characteristic response function in the step 2 is based on the following formula:
wherein: TF (j) represents a pore wall texture feature response function value corresponding to the j-th column of the pore wall expansion image F4, and the pore wall texture feature responseRepresenting the red image gradient corresponding to the j-th column of the hole wall expanded image F4; />Representing the green image gradient corresponding to the j-th column of the hole wall expanded image F4; />Representing the blue image gradient corresponding to the j-th column of the hole wall expanded image F4;
the pore wall integrity characteristic response function in the step 2 is based on the following formula:
wherein IF (j) represents a hole wall integrity feature response function value, max { S }, of a j-th column of the hole wall expansion image F4 r (j) The red gray maximum value corresponding to the RGB value of the j-th pixel point in the hole wall expanded image F4 is min { S }, and r (j) The j-th column in the image F4 is developed for the hole wallRed gray minimum value corresponding to RGB value of pixel point, NN is total line number of pixel point of hole wall expansion image F4, N n Representing the total number of columns of the matrix of pixel points of the hole wall expansion image F3,the average value S of blue gray scale corresponding to RGB value of j-th column pixel point in the hole wall unfolded image F4 b (m, n) is a blue gray value corresponding to the RGB value of the pixel point in the m-th row and n-th column in the hole wall expansion image F4;
the echo signal time domain characteristic response function in the step 2 is based on the following formula:
wherein CF (j) represents the time domain characteristic response function value of the echo signal corresponding to the j-th column echo signal in the acoustic wave scanning matrix TT, c is the sound velocity corresponding to the acoustic wave propagation medium in the borehole, D is the diameter of the upper shell, and D is the diameter of the geological borehole, t| j Representing the time corresponding to the first occurrence of echo of the jth column echo signal in the acoustic wave scanning matrix TT;
the echo signal spectrum characteristic response function in the step 2 is based on the following formula:
wherein AF (j) represents the spectral characteristic response function value of the echo signal corresponding to the j-th echo signal in the acoustic wave scanning matrix TT, fmax represents the maximum frequency corresponding to the bandwidth of the acoustic wave signal, fmin represents the minimum frequency corresponding to the bandwidth of the acoustic wave signal, and E (f) | j And representing the acoustic characteristic function value corresponding to the j-th column echo signal in the acoustic wave scanning matrix TT.
4. The method for identifying a weak interlayer based on intra-hole optical imaging and acoustic wave scanning according to claim 3, wherein the step 3 comprises the following steps:
step 3.1, dividing the hole wall expansion image F4 into M+1 rows of equidistant hole wall sub-images to form normalized hole wall expansion images, wherein each row of hole wall sub-images comprises N n The pixel points of the column/M,
normalized hole wall expanded image each row of hole wall texture feature response function value takes N corresponding to hole wall expanded image F4 n An average value of pore wall texture characteristic response function values of M columns of pixel points,
the pore wall integrity characteristic response function value of each row of normalized pore wall expansion image is obtained as the average value of the pore wall integrity characteristic response function values of N/M rows of pixel points corresponding to the pore wall expansion image F4, the pore wall azimuth angle represented by each row of image is 2 pi/M,
step 3.2, obtaining a borehole wall reconstruction image F5 based on the following formula:
F5(p,q)＝δ 1 ·TF(p,q)+δ 2 ·IF(p,q)+δ 3 ·AF(p,q)+δ 4 ·CF(p,q)
wherein delta 1 、δ 2 、δ 3 、δ 4 Weighting values, delta, respectively, of different response functions 1 +δ 2 +δ 3 +δ 4 =1, F5 (p, q) is the pixel value of the depth p column number q of the borehole wall reconstruction image, TF (p, q) is the hole wall texture feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, IF (p, q) is the hole wall integrity feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, AF (p, q) is the echo signal spectral feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q, CF (p, q) is the echo signal time domain feature response function value of the normalized hole wall expansion image corresponding to the depth p column number q,
Step 3.3, if the average value of pixels of a certain depth of the borehole wall reconstruction image F5 is smaller than a set threshold value, the depth is considered to be a weak interlayer region; if the average value of the pixels of a depth of the borehole wall reconstruction image F5 is greater than or equal to a set threshold, the depth is considered to be a non-weak region.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211419778.7A CN115793091B (en) | 2022-11-14 | 2022-11-14 | Weak interlayer identification method and device based on in-hole optical imaging and acoustic wave scanning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211419778.7A CN115793091B (en) | 2022-11-14 | 2022-11-14 | Weak interlayer identification method and device based on in-hole optical imaging and acoustic wave scanning |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115793091A CN115793091A (en) | 2023-03-14 |
| CN115793091B true CN115793091B (en) | 2023-11-17 |
Family
ID=85437394
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211419778.7A Active CN115793091B (en) | 2022-11-14 | 2022-11-14 | Weak interlayer identification method and device based on in-hole optical imaging and acoustic wave scanning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115793091B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106154350A (en) * | 2016-06-16 | 2016-11-23 | 山东大学 | Engineering comprehensive gaging hole System and method for based on shooting in hole with single-hole sound-wave |
| GB201910288D0 (en) * | 2013-03-11 | 2019-09-04 | Reeves Wireline Tech | Methods of and apparatuses for identifying geological characteristics in boreholes |
| CN111608644A (en) * | 2020-05-06 | 2020-09-01 | 中国科学院武汉岩土力学研究所 | Array type acoustic scanning high-precision drilling imaging method and device |
| CN113985492A (en) * | 2021-09-09 | 2022-01-28 | 中国科学院武汉岩土力学研究所 | Photoacoustic fusion multi-scale detection method for geology around drill hole and related device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1867833B1 (en) * | 2006-06-15 | 2009-04-29 | Services Pétroliers Schlumberger | Apparatus and method for obtaining images of a borehole |
-
2022
- 2022-11-14 CN CN202211419778.7A patent/CN115793091B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB201910288D0 (en) * | 2013-03-11 | 2019-09-04 | Reeves Wireline Tech | Methods of and apparatuses for identifying geological characteristics in boreholes |
| CN106154350A (en) * | 2016-06-16 | 2016-11-23 | 山东大学 | Engineering comprehensive gaging hole System and method for based on shooting in hole with single-hole sound-wave |
| CN111608644A (en) * | 2020-05-06 | 2020-09-01 | 中国科学院武汉岩土力学研究所 | Array type acoustic scanning high-precision drilling imaging method and device |
| CN113985492A (en) * | 2021-09-09 | 2022-01-28 | 中国科学院武汉岩土力学研究所 | Photoacoustic fusion multi-scale detection method for geology around drill hole and related device |
Non-Patent Citations (2)
| Title |
|---|
| 3D reconstruction and characterization of reef limestone pores based on optical and acoustic microscopic images;Jinchao Wang et al;Marine Georesources & Geotechnology;第44卷(第9期);全文 * |
| fine detection technology of rock mass structure based on borehole acousto-optic combined measurement;Jinchao Wang et al;Measurement;第187卷(january);第2、6、16、18页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115793091A (en) | 2023-03-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110208859B (en) | Intelligent calculation method for quantitative parameters of oil-based mud well fractures based on ultrasonic imaging | |
| US20190055830A1 (en) | Well integrity analysis using sonic measurements over depth interval | |
| CN109685011A (en) | A kind of underground utilities detection recognition method based on deep learning | |
| CN111781146B (en) | Wave parameter inversion method using high-resolution satellite optical image | |
| CN107247927B (en) | Method and system for extracting coastline information of remote sensing image based on tassel cap transformation | |
| US11604301B2 (en) | Methods and systems for automated sonic imaging | |
| CN114548278A (en) | In-service tunnel lining structure defect identification method and system based on deep learning | |
| CN110689512B (en) | Method for quickly splicing and fusing annular images of panoramic video in hole into image | |
| CN108267427B (en) | Seabed sediment spectral measurement method and device and terminal | |
| US11789173B1 (en) | Real-time microseismic magnitude calculation method and device based on deep learning | |
| CN105241428A (en) | Water depth retrieval method with hyper-spectrum | |
| CN113685188A (en) | TBM tunneling optimization method based on physical characteristics of rock slag | |
| CN115330664A (en) | Image recognition-based surrounding rock weathering degree full-automatic recognition method and device | |
| CN116295285A (en) | Shallow sea water depth remote sensing inversion method based on region self-adaption | |
| CN112801035B (en) | Knowledge and data dual-drive-based carrying type lithology intelligent identification method and system | |
| CN115793091B (en) | Weak interlayer identification method and device based on in-hole optical imaging and acoustic wave scanning | |
| CN114942436A (en) | Tunnel lining disease identification method and system based on geological radar and deep learning | |
| US20230386069A1 (en) | Rock crack information identification method and system based on variational autoencoder | |
| US20230306578A1 (en) | Ultrasonic defect detection and classification system using machine learning | |
| CN102505938B (en) | Well periphery ultrasonic imaging downhole cartridge scanning head | |
| CN115375925A (en) | Underwater sonar image matching algorithm based on phase information and deep learning | |
| Liu et al. | Advances in automatic identification of road subsurface distress using ground penetrating radar: State of the art and future trends | |
| CN111119870A (en) | Drilling surrounding rock structure detection device and method based on sound wave circumferential scanning | |
| CN112270301A (en) | Landsat remote sensing image water body extraction method based on wave band characteristics | |
| CN115749734B (en) | Method for learning geological structure on line by ultrasonic imaging logging while drilling instrument |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |